It has been known for some time that classical interpolation techniques, such as linear and bi-cubic interpolation, are not good performers since these methods tend to blur and create jaggedness in edges. Wavelets have been used in interpolation with mixed results. These methods assume the image has been passed through a low pass filter before decimation and then try to estimate the missing details, or wavelet coefficients, from the low resolution scaling coefficients. One drawback to these approaches is that they assume the knowledge of the low pass filter. A second and more severe drawback is that the image model these methods assume depends heavily on the assumption that the fine detail coefficients are known, which in the interpolation case are not. Directional interpolation processes try to first detect edges and then interpolate along edges, avoiding interpolation across edges. In this class, there are processes that do not require the explicit detection of edges. Rather the edge information is built into the process itself. The drawbacks with most processes we have tested, including the ones mentioned above, is that the processes' focus seems to be on producing sharp images rather than trying to eliminate jagged edges. When processes do focus on maintaining edge integrity images often times look too much like drawings, especially for large enlargement factors.
Two patents that remotely resemble our work are patent numbers WO9956247 and U.S. Pat. No. 6,075,926, although their approach to image interpolation is quite different than ours. Our invention has the advantage of interpolating by the scale factor in one step. In other words, interpolation by 8 is done in one step, as opposed to applying an interpolation by 2 process three times.